Detection Event Log¶
Class: DetectionEventLogBlockV1
Source: inference.core.workflows.core_steps.analytics.detection_event_log.v1.DetectionEventLogBlockV1
This block maintains a log of detection events from tracked objects. For each tracked object it records: class name, first and last seen frame numbers, absolute wall-clock timestamps (Unix epoch floats derived from frame_timestamp metadata, or time.time() as fallback), and relative timestamps in seconds since the video started. Objects must be seen for a minimum number of frames (frame_threshold) before being moved from 'pending' to 'logged' status. Stale events (not seen for stale_frames frames) are removed during periodic cleanup (every flush_interval frames). When a logged event goes stale it is emitted in the complete_events output, which contains the full event data for objects that were tracked long enough to be logged and have since left the scene. The reference_timestamp parameter is deprecated and no longer used.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/detection_event_log@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
frame_threshold |
int |
Number of frames an object must be seen before being logged.. | ✅ |
flush_interval |
int |
How often (in frames) to run the cleanup operation for stale events.. | ✅ |
stale_frames |
int |
Remove events that haven't been seen for this many frames.. | ✅ |
reference_timestamp |
float |
Deprecated, no longer used. Absolute timestamps are now taken directly from frame_timestamp metadata (or time.time() as fallback).. | ✅ |
fallback_fps |
float |
Fallback FPS to use when video metadata does not provide FPS information. Used to calculate relative timestamps.. | ✅ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow runtime. See Bindings for more info.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to Detection Event Log in version v1.
- inputs:
Time in Zone,Moondream2,Identify Changes,Instance Segmentation Model,Object Detection Model,Cosine Similarity,Byte Tracker,Detections Stitch,SAM2 Video Tracker,Motion Detection,Time in Zone,SAM 3,Perspective Correction,Detections Classes Replacement,Velocity,Dynamic Zone,Detections List Roll-Up,Instance Segmentation Model,Detections Combine,Detections Consensus,Detection Offset,Dynamic Crop,SAM 3,ByteTrack Tracker,Overlap Filter,Template Matching,PTZ Tracking (ONVIF),Detections Stabilizer,Byte Tracker,VLM As Detector,EasyOCR,Segment Anything 2 Model,Detections Merge,Camera Focus,SAM 3,Gaze Detection,Camera Focus,Seg Preview,Detections Transformation,Byte Tracker,Line Counter,YOLO-World Model,Bounding Rectangle,SORT Tracker,OC-SORT Tracker,OCR Model,Detection Event Log,Mask Area Measurement,Object Detection Model,Object Detection Model,Path Deviation,Detections Filter,Time in Zone,Google Vision OCR,VLM As Detector,Instance Segmentation Model,Path Deviation - outputs:
Icon Visualization,Slack Notification,Label Visualization,Instance Segmentation Model,Dot Visualization,Trace Visualization,Time in Zone,Roboflow Custom Metadata,Dynamic Zone,Image Threshold,Keypoint Visualization,Overlap Filter,PTZ Tracking (ONVIF),Blur Visualization,Circle Visualization,Keypoint Detection Model,Crop Visualization,Detections Merge,Email Notification,Classification Label Visualization,Identify Outliers,Twilio SMS Notification,Twilio SMS/MMS Notification,Model Monitoring Inference Aggregator,Keypoint Detection Model,Anthropic Claude,Path Deviation,Detections Filter,Time in Zone,Distance Measurement,Stability AI Inpainting,Model Comparison Visualization,Byte Tracker,SAM2 Video Tracker,Motion Detection,Detections Classes Replacement,Detections List Roll-Up,Florence-2 Model,Size Measurement,Detection Offset,Dynamic Crop,SAM 3,SIFT Comparison,Detections Stabilizer,Byte Tracker,Grid Visualization,Polygon Visualization,Mask Visualization,Webhook Sink,Image Slicer,Bounding Rectangle,SORT Tracker,OC-SORT Tracker,Detection Event Log,Object Detection Model,Object Detection Model,Roboflow Dataset Upload,Object Detection Model,Detections Stitch,Morphological Transformation,Perspective Correction,Instance Segmentation Model,Florence-2 Model,Detections Combine,Anthropic Claude,Image Slicer,Absolute Static Crop,Email Notification,Polygon Visualization,Stitch OCR Detections,Color Visualization,Line Counter,Byte Tracker,Image Contours,Mask Area Measurement,Roboflow Vision Events,Instance Segmentation Model,Time in Zone,Triangle Visualization,Pixel Color Count,Stitch OCR Detections,Background Color Visualization,Identify Changes,Line Counter,Anthropic Claude,Image Blur,Stitch Images,Dominant Color,Corner Visualization,Velocity,Halo Visualization,Detections Consensus,Reference Path Visualization,Line Counter Visualization,ByteTrack Tracker,Keypoint Detection Model,Roboflow Dataset Upload,Heatmap Visualization,Text Display,Segment Anything 2 Model,Camera Focus,Detections Transformation,Image Preprocessing,SIFT Comparison,Bounding Box Visualization,Stability AI Outpainting,Halo Visualization,Background Subtraction,QR Code Generator,Pixelate Visualization,Ellipse Visualization,Path Deviation
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Detection Event Log in version v1 has.
Bindings
-
input
image(image): Reference to the image for video metadata (frame number, timestamp)..detections(Union[object_detection_prediction,instance_segmentation_prediction]): Tracked detections from byte tracker (must have tracker_id)..frame_threshold(integer): Number of frames an object must be seen before being logged..flush_interval(integer): How often (in frames) to run the cleanup operation for stale events..stale_frames(integer): Remove events that haven't been seen for this many frames..reference_timestamp(float): Deprecated, no longer used. Absolute timestamps are now taken directly from frame_timestamp metadata (or time.time() as fallback)..fallback_fps(float): Fallback FPS to use when video metadata does not provide FPS information. Used to calculate relative timestamps..
-
output
event_log(dictionary): Dictionary.detections(Union[object_detection_prediction,instance_segmentation_prediction]): Prediction with detected bounding boxes in form of sv.Detections(...) object ifobject_detection_predictionor Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object ifinstance_segmentation_prediction.total_logged(integer): Integer value.total_pending(integer): Integer value.complete_events(dictionary): Dictionary.
Example JSON definition of step Detection Event Log in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/detection_event_log@v1",
"image": "$inputs.image",
"detections": "$steps.byte_tracker.tracked_detections",
"frame_threshold": 5,
"flush_interval": 30,
"stale_frames": 150,
"reference_timestamp": 1726570875.0,
"fallback_fps": 1.0
}